[Feature] add multi-source sampler

[Tau-J]

Motivation

Sampling data from CombinedDataset with specified source ratio

Modification

BC-breaking (Optional)

Use cases (Optional)

Checklist

Before PR:

• [ ] I have read and followed the workflow indicated in the CONTRIBUTING.md to create this PR.
• [ ] Pre-commit or linting tools indicated in CONTRIBUTING.md are used to fix the potential lint issues.
• [ ] Bug fixes are covered by unit tests, the case that causes the bug should be added in the unit tests.
• [ ] New functionalities are covered by complete unit tests. If not, please add more unit tests to ensure correctness.
• [ ] The documentation has been modified accordingly, including docstring or example tutorials.

After PR:

• [ ] CLA has been signed and all committers have signed the CLA in this PR.

[ly015]

@Tau-J Could you please add unit tests for multi-source sampler?

[codecov[bot]]

Codecov Report

Base: 80.35% // Head: 80.07% // Decreases project coverage by -0.29% :warning:

Coverage data is based on head (4f2a8d5) compared to base (07715a5). Patch coverage: 31.57% of modified lines in pull request are covered.

:exclamation: Current head 4f2a8d5 differs from pull request most recent head 7d14532. Consider uploading reports for the commit 7d14532 to get more accurate results

Additional details and impacted files

@@             Coverage Diff             @@
##           dev-1.x    #1938      +/-   ##
===========================================
- Coverage    80.35%   80.07%   -0.29%     
===========================================
  Files          209      210       +1     
  Lines        12463    12519      +56     
  Branches      2105     2112       +7     
===========================================
+ Hits         10015    10024       +9     
- Misses        1996     2043      +47     
  Partials       452      452              

Flag	Coverage Δ
unittests	80.07% <31.57%> (-0.29%)	:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
mmpose/datasets/samplers.py	29.09% <29.09%> (ø)
mmpose/datasets/__init__.py	100.00% <100.00%> (ø)
mmpose/codecs/associative_embedding.py	92.50% <0.00%> (-3.75%)	:arrow_down:
mmpose/datasets/transforms/common_transforms.py	85.21% <0.00%> (-0.58%)	:arrow_down:

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